Control units are electronic modules, which are used in motor vehicles for control and/or regulation processes. Toward this end, functionalities, normally realized in the form of software and executed on a processor or CPU in the control unit, are implemented in the control unit.
The application of control units means populating the control units with data. In this context the populating with data denotes the inputting or copying of data into or onto a data-storing entity, in most cases a storage device in the control unit.
One working step in the application in engine control units is what is known as the basic adaptation. During the basic adaption, for example, data for engine control functions for detecting the cylinder charge are input. Tools for optimizing all identifiers or labels of such a function are used for this purpose.
A great number of measurements, which are usually determined on an engine test bench, are required for the input into these tools, for which in addition to basic influencing parameters of engine speed and load, further influencing quantities in accordance with the provided charge actuators, such as camshaft angle positions (intake and discharge camshaft), exhaust-gas recirculation rates, intake manifold switchovers, charge motion valve positions, etc., are varied. From the related art, “Design of Experiments” (DoE) methods are known, which instead of employing a grid measurement of all influencing parameters to be varied, use a certain selection of necessary measurements per operating point, defined by engine speed and load, in order to adapt a local operating point model such as a polynomial model (cornerstone) on that basis. These models are then able to be queried only at the operating points, but not in-between.
Populating the labels of a function such as the charge detection, for example, with data requires measurements across the entire operating range, which have to be carried out with the necessary precision. To keep the number of measurements low nevertheless, a so-called global data-based model is inserted between measurements on the test stand and the optimization tool. Virtual measurements using all kinds of variations of the influencing parameters are then carried out on this model.
A method for developing a global model of an output parameter for a dynamic system is known from the International Published Patent Appln. WO 2006/051039. This could be an operating parameter of an internal combustion engine, for instance. This method is to make it possible to manage with only a small number of measuring points for calculating the output parameter for all states. In the development of the global model, a development of the input variable with polynomials takes place and a calculation of coefficients of the development. In the printed publication it is furthermore described to determine variances at measuring points by way of repeat measurements. Parallel to the model of the data, these variances are used for setting up a second model of the variances. This makes it possible to describe in which areas the measurements are more precise and in which areas the measurements are less precise.